The evaluation of country risk and economic potential

The need for a framework to evaluate the risks inherent in dealing with different countries is widely recognized. International financial institutions, government agencies and major corporations have in recent years established formal systems of risk assessment as an important input to their operational and planning decisions. It is important to understand the basic thinking underlying the mechanical approach to risk analysis and the results must be treated with care. A structured approach to the evaluation of international risks provides the necessary analytical framework.     

基于可变精度粗糙集的新兴技术企业信用风险识别

针对新兴技术企业信用风险评估的必要性和现有评估方法仅局限于财务指标且指标之间高度相关的缺点,借鉴了可变精度粗糙集（VPRS）模型具有噪声数据的强适应能力和强抗干扰能力的优点,提出了一类基于VPRS的新兴技术企业信用风险识别方法,并用已上市的部分新兴技术企业对其进行实证检验,检验结果表明了该方法具有较好的识别能力。该方法首先运用VPRS理论的最新研究成果,并借助于粗糙集分析软件ROSETYA,对由训练样本组成的数据关系表进行数据补缺、离散化及属性的β约简等处理,从而导出识别规则,形成识别规则库;然后集成二叉树构建一类新兴技术企业信用风险识别方法;最后用测试样本对方法的识别精度进行检验。     

资金紧缺型企业规避风险时的决策行为分析

现实中许多企业（尤其中小企业）往往需要通过各种融资手段获取资金以支持其日常运作。融资在为企业带来运作资金的同时,也增加了企业的财务风险。通过在经典报童模型中引入企业的财务状态,综合分析了企业的最优运作决策与财务决策,以及企业决策者对待风险的态度（风险中性、损失规避等）对其决策行为的影响。研究发现,与风险中性型零售商相比,在一定条件下,损失规避型零售商能够在不降低企业期望收益的前提下降低企业的财务风险。     

Measurement and Pricing of Risk in Insurance Markets

The theory and practice of risk measurement provides a point of intersection between risk management, economic theories of choice under risk, financial economics, and actuarial pricing theory. This article provides a review of these interrelationships, from the perspective of an insurance company seeking to price the risks that it underwrites. We examine three distinct approaches to insurance risk pricing, all being contingent on the concept of risk measures. Risk measures can be interpreted as representations of risk orderings, as well as absolute (monetary) quantifiers of risk. The first approach can be called an "axiomatic" one, whereby the price for risks is calculated according to a functional determined by a set of desirable properties. The price of a risk is directly interpreted as a risk measure and may be induced by an economic theory of price under risk. The second approach consists in contextualizing the considerations of the risk bearer by embedding them in the market where risks are traded. Prices are calculated by equilibrium arguments, where each economic agent's optimization problem follows from the minimization of a risk measure. Finally, in the third approach, weaknesses of the equilibrium approach are addressed by invoking alternative valuation techniques, the leading paradigm among which is arbitrage pricing. Such models move the focus from individual decision takers to abstract market price systems and are thus more parsimonious in the amount of information that they require. In this context, risk measures, instead of characterizing individual agents, are used for determining the set of price systems that would be viable in a market.     

Impact of strategic and operational risk management practices on firm performance: An empirical investigation

Increasingly, creating and delivering value through complex supply chain networks involves substantial risks. However, strategy development under business risk conditions is not well-understood. This cross-country research examines how, under conditions of supply chain network risk, firms develop effective risk management practices. Using a literature review and survey research of managers from global firms; we present a research model, and empirically test the hypothesized relationships. The results show that under conditions of uncertainty, management decision-making is more likely to be cautious until visible forms of risks emerge, and prudent response mechanisms are put in place. This study identifies the crucial role of supply chain exploration and exploitation practices, and their influence in development of network risk management practices, leading to competitive financial outcomes.     

动态尾部金融网络结构与传染性度量

基于Lasso高维分位数回归模型,本文构建了中国金融系统的尾部网络结构,并定义了总体网络以及行业间、行业内和金融机构间等多层金融网络的尾部风险传染度,解构其传染机制与关联特征,评估各机构双向系统重要性(接收端和发射端)。同时,本文提出了一个最优滚动窗宽选择标准方法,以优化滚动样本技术下的动态网络结构。结果表明,所有层级尾部风险传染效应(总体系统、行业间、行业内和机构间)在经济金融极端困境时期,呈现明显增强及剧烈震荡特征,2015年中国股灾期间尤甚。跨行业传染效应日益严峻,银行与保险间表现出较强关联性,房地产机构与其他金融机构间均表现出较高传染性,跨业监管值得关注。接收与发射最多尾部风险传染的金融机构仍然是银行与证券类机构。系统中超过50%的金融机构倾向于接收风险传染,一旦出现系统性冲击,整个金融系统的稳定性将遭受重创,因此,应加强此类机构应对外界冲击的能力。此外,基于新滚动窗宽选择标准法的动态模型的估计性能明显优于传统方法。研究结论有助于理解中国金融系统的网络结构和传染机制,对宏观审慎监管体系的建立提供了依据。     

Managing Risk: A Joint U.S.-German Perspective

Ideas from a USA-FRG conference on risk management are presented. In general, the difficulties confronted by risk management authorities in the two countries are similar, from discovering important risks at an early stage to setting acceptable goals. Government regulation is overburdened and somewhat inefficient in both countries, leading to greater search for alternatives. The many differences in approach between the two countries can inform both. German risk management is done largely through negotiations among the affected parties; when this does not resolve a dispute, a specialized administrative court takes charge. In both countries nonregulatory methods of managing risk should be enhanced and given a larger role. A matrix of risk management method versus criteria proved stimulating in comparing and ranking approaches. The conceptual differences between managing discrete events (auto crashes, boiler explosions, etc.) and chronic exposures have not been appreciated. Although uncertainty and probability are involved in both, there are qualitative differences in both analysis and management. Public perceptions of risk and the role these should play have been characterized by "objectivist" and "subjectivist" positions. In the former view, risks are subject to analysis, are calculable, and the public must be educated to accept the conclusions of experts. In the latter view what people perceive is what is most important, both psychologically and politically, and the risk experts must understand public fears and desires. These are important opportunities for cross cultural studies.     

Supply chain multi-state risk assessment using universal generating function

Abstract

This paper proposes a new approach to assess the supply risk beyond the classical binary assumption of either delivering the whole quantity or not. Given today’s stochastic nature of supply and the dynamic nature of demand, the different supply activities along with the chain exhibit a multi-state behaviour increasing the complexity of their risk assessment. The new approach utilizes the universal generating function (UGF) to model the different suppliers’ echelons with their various supply risk levels along all the stages of the supply chain as a multi-state risk system. The developed model was successfully implemented to assess the supply risk in a multi-state strawberry supply chain and outperformed classical approaches. Results from the case study and the validation analysis illustrated the ability of the new approach to capture the various supply levels with their associated risks leading to more informative risk assessment process. Furthermore, the developed model improved the visibility for the purchasing managers downstream in terms of the different trade-offs between supply levels and their risks as well as some financial thresholds. The new multi-state approach contributes to the emerging supply chain risk assessment trend by offering a more realistic modelling method to capture the risk of all available supply levels along the delivery chain.     

The Impact of Mega‐Catastrophes on Insurers: An Exposure‐Based Analysis of the U.S. Homeowners’ Insurance Market

Insurance is a key risk‐sharing mechanism that protects citizens and governments from the losses caused by natural catastrophes. Given the increase in the frequency and intensity of natural catastrophes over recent years, this article analyzes the performance effects of mega‐catastrophes for U.S. insurance firms using a measure of market expectations. Specifically, we analyze the share price losses of insurance firms in response to catastrophe events to ascertain whether mega‐catastrophes significantly damage the performance of insurers and whether different types of mega‐catastrophes have different impacts. The main message from our analysis is that the impact of mega‐catastrophes on insurers has not been too damaging. While the exact impact of catastrophes depends on the nature of the event and the degree of competition within the relevant insurance market (less competition allows insurers to recoup catastrophe losses through adjustments to premiums), our overall results suggest that U.S. insurance firms can adequately manage the risks and costs of mega‐catastrophes. From a public policy perspective, our results show that insurance provides a robust means of sharing catastrophe losses to help reduce the financial consequences of a catastrophe event.     

中国股市跨行业系统性风险空间溢出关联及风险预测分析——基于尾部风险网络模型

基于条件风险价值CoVaR和SIM单指数分位数回归技术,选取2012-2018年我国股市24行业指数周频数据,构建时变的跨行业尾部风险网络,通过网络拓扑结构反映系统性风险的空间关联及潜在变化趋势。此外,引入ARDL模型探究网络结构和宏观经济变量对股市系统性风险的长短期效应,最后对系统性风险进行预测。结果表明：(1)我国股市行业板块间存在明显的系统性风险空间关联和传染效应,风险溢出网络具有“小世界”特征;(2)网络连边集中度HHI呈明显的周期性变化。在尾部事件期间,HHI指标显著增加,风险网络呈较单一的中心节点结构,网络稳定性差;(3)通过节点风险传播强度和中心化程度发现,仅通过节点内部属性判断节点的系统重要性已不够全面和准确,应结合节点在网络中的位置和关联关系来判断;信息技术、医疗保健、商业和专业服务行业是风险网络中最有影响力的行业;(4)通过ARDL-ECM模型发现网络连边集中度是系统性风险的主要影响因素,并对股市系统性风险进行了高度准确的预测。本研究可为监管机构有效识别我国股市中有影响力的行业提供参考,依据关键行业的溢出关联制定针对性的风险防范措施,同时对风险溢出效应设立预警机制。     

基于改进教学式方法的可解释信用风险评价模型构建

信用风险评价是金融机构风险防控的重要环节之一。近年来，基于机器学习的信用风险评价模型以其准确的预测效果受到越来越多的关注，但机器学习模型具有可解释性不强的弊端，导致投资者无法完全信任其预测结果。针对上述问题，本文提出了一种改进的教学式方法，利用机器学习模型指导生成一个兼顾准确性与可解释性的信用风险评价决策树模型，以辅助投资者决策。为提高决策树对机器学习模型中正确功能的学习能力，提出了基于Weight Synthetic Minority Over-sampling Technique（Weight-SMOTE）的伪数据集生成方法，以提高伪数据集中可信度高的功能所标记的伪样本比例；为实现所生成的决策树在准确性、可解释性以及其与机器学习模型一致性间的有效权衡，在决策树生成过程中提出了一种新的决策树剪枝方法；同时针对保真度评价指标的局限性，提出了真保真度评价指标，来有效的衡量决策树与机器学习模型正确功能的近似程度。最后使用3个真实信用风险评价数据集对改进的教学式方法进行验证，实验结果表明所提出方法能够生成准确且可解释的信用风险评价模型，以满足投资者的决策偏好与实际需求。     

基于非参数Copula-CVaR模型的碳金融市场集成风险测度

我国商业银行等金融机构在参与国际碳金融业务时面临复杂多变的市场环境,其风险评估及预警体系的构建需考虑风险因子的多源性与相依性,对碳金融市场集成风险进行科学测度具有重要意义。本文采用非参数核估计方法确定碳金融市场价格波动与汇率波动两类风险因子的边缘分布,并通过拟合优度检验选择最优Copula函数准确刻画风险因子之间非线性、动态的相依结构,实现对集成条件风险价值CVaR的有效测度。通过Kupiec回测检验及对比各类传统风险测度方法的优劣,发现非参数Copula-CVaR模型能够弥补传统风险测度方法在度量多源风险因子相依性时存在的局限性,避免参数法确定边缘分布时可能出现的模型设定风险与参数估计误差,充分考虑尾部风险,为碳金融市场集成风险测度提供新思路。     

Risk assessment of outsourcing e-procurement services: integrating SWOT analysis with a modified ANP-based fuzzy inference system

With electronic procurement solutions becoming increasingly sophisticated, many firms opt to source these services from third-party providers, effectively transferring (outsourcing) significant responsibility to these services companies. This action, however, entails certain risks, which are oftentimes difficult to assess. To guide managerial practice and to advance academic inquiry in this domain, we identify e-procurement risk factors through a strengths, weaknesses, opportunities, threats analysis, grounded in transaction cost economics (TCE), and propose a risk assessment framework based on the opinions of a group of experts. The approach taken is that of a modified analytic network process methodology, combined with a fuzzy inference system, which is versatile enough to accept the expert opinions in different input formats (such as linguistic variables and ranges). The proposed framework has the capability to aggregate expert judgements’ to estimate risk likelihoods, risk severities and risk factor indices, and derive overall risk magnitudes. The multi-method approach was motivated and is illustrated by a real-life case study of an Indian manufacturing company currently in the process of contract renewal with its existing e-procurement service provider.     

极端情况下对我国股市风险的实证研究

准确地度量风险是对风险进行有效管理的前提也是投资者做出合理的投资决策的基础,然而在极端事件频繁发生的情况下,传统的VaR计算方法难以准确地度量股市风险,极值理论却可以很好地解决这一问题。本文特别关注了由2007年美国"次贷" 危机所引发的全球金融危机爆发时我国股市的风险度量问题,考虑到全球股市间极端事件的联动效应,利用基于极值理论的POT模型对上证综指日收益率的尾部数据直接建模拟合分布,进而计算出风险值VaR和CVaR,通过比较危机前后的风险值,发现随着金融危机的到来,我国股市的风险有了一定程度的释放。     

Embracing risk as a core competence: The case of CEMEX

In this paper we argue that risk management can be an important source of competitive advantage for firms. For this to happen, managers must overcome four deep-seated notions about the management of risk: the myopic conception that risk is a collection of unconnected threats to the survival of a firm, the belief that risk management is largely a financial activity, the idea that risk management is solely a top management team task, and a blind faith that CEOs can continuously anticipate the risks that firms must address on an ongoing basis. Challenging these four misconceptions reveals that risk management can be an activity that is value creating, not just value preserving. Indeed, rather than indiscriminately shedding all types of risks, companies can develop new sources of competitive advantage by embracing those risks that they are relatively better at managing than their rivals. We illustrate our arguments by analyzing the risk management practices at CEMEX, the Mexican cement manufacturer.     

基于LGCNET多层网络的中国A股上市公司系统性风险度量

系统性风险度量一直是金融风险领域的热点问题,但是对于复杂网络条件下的度量方法还缺乏深入研究。本文将滑动窗口分位数回归与局部高斯相关方法相结合,构建出一种全新的多层时变网络——局部高斯相关网络(Local Gaussian Correlation Network, LGCNET)。基于此方法,本文通过研究中国证券市场股票总体及尾部收益的非线性相关性,分析了2018年至2021年我国A股50家上市企业关联网络的演化特征,通过考察金融网络系统性风险水平在整个时间段内的变化情况,探究了新冠疫情及中美贸易摩擦期间上市公司网络的风险变化情况。结果表明：第一,金融与科技行业是网络节点的中心,与其他行业公司存在较高关联性,表明该类行业是风险传导的中心。第二,基建及银行类公司因为其市值高,在系统中的重要程度普遍较高;同时,尾部风险排名高于其市值排名的企业具有较大市场影响力和风险传导能力,也应该受到关注。第三,在系统层面,受信用风险加剧及中美贸易摩擦的影响,2018年整个网络系统普遍具有较高风险水平;但在2020年新冠疫情期间,国内系统性风险一直控制在较低水平。     

Applying the Partitioned Multiobjective Risk Method (PMRM) to Portfolio Selection

The analysis of risk-return tradeoffs and their practical applications to portfolio analysis paved the way for Modern Portfolio Theory (MPT), which won Harry Markowitz a 1992 Nobel Prize in Economics. A typical approach in measuring a portfolio's expected return is based on the historical returns of the assets included in a portfolio. On the other hand, portfolio risk is usually measured using volatility, which is derived from the historical variance-covariance relationships among the portfolio assets. This article focuses on assessing portfolio risk, with emphasis on extreme risks. To date, volatility is a major measure of risk owing to its simplicity and validity for relatively small asset price fluctuations. Volatility is a justified measure for stable market performance, but it is weak in addressing portfolio risk under aberrant market fluctuations. Extreme market crashes such as that on October 19, 1987 ("Black Monday") and catastrophic events such as the terrorist attack of September 11, 2001 that led to a four-day suspension of trading on the New York Stock Exchange (NYSE) are a few examples where measuring risk via volatility can lead to inaccurate predictions. Thus, there is a need for a more robust metric of risk. By invoking the principles of the extreme-risk-analysis method through the partitioned multiobjective risk method (PMRM), this article contributes to the modeling of extreme risks in portfolio performance. A measure of an extreme portfolio risk, denoted by f(4), is defined as the conditional expectation for a lower-tail region of the distribution of the possible portfolio returns. This article presents a multiobjective problem formulation consisting of optimizing expected return and f(4), whose solution is determined using Evolver-a software that implements a genetic algorithm. Under business-as-usual market scenarios, the results of the proposed PMRM portfolio selection model are found to be compatible with those of the volatility-based model. However, under extremely unfavorable market conditions, results indicate that f(4) can be a more valid measure of risk than volatility.     

FINANCIAL DEPENDENCE,BANKING SECTOR COMPETITION,AND ECONOMIC GROWTH

The relationships among competition in the financial sector, access of firms to external financing, and associated economic growth are ambiguous in theory. Moreover, measuring competition in the financial sector can be complex. In this paper we first estimate for 16 countries an industrial organization‐based measure of banking system competition. We then relate this competition measure to growth of industries and find that greater competition in countries' banking systems allows financially dependent industries to grow faster. These results are robust under a variety of tests. Our results suggest that the degree of competition is an important aspect of financial sector functioning. (JEL: D4, G21, L11, L80, O16)     

对企业实行债转股的思考

启动财务杠杆给企业带来的效益一直是理论界关注的焦点.本文所介绍的是在西方较为流行的两种对启动财务杠杆实行馈转股的企业进行效益分析的理论模型.第—种模型强调资本成本在债转股中的重要性,认为企业制订是否实行债转股的决策依据就是对企业破产成本,委托代理成本和无形资产成本的评估.而对投资者来说,在投资中选择持债还是持股也依据他们对委托代理成本和无形资产的评估.第二种模型则建议企业在启动资本杠杆实行债转股中注重对风险的规避. 对于中国国有企业实行的债转股,本文以为它在所有制、市场条件及社会经济制度背景等方面具有完全不同的性质.但我们仍可以利用财务杠杆的工作原理将国有企业的债务转为股份公开上市交易,以实行中国国有企业的民营化,减轻企业的债务负担,同时减少国有银行的呆坏帐.     

嵌入网络舆情指数的中国金融机构系统性风险传染效应研究

首先基于文本挖掘技术构建反映投资者情绪的网络舆情指数,然后将所构建的网络舆情指数嵌入到系统性风险传染效应度量模型,得到修正的单指标非对称CoVaR模型,并运用线性分位数LASSO算法与局部多项式估计方法进行参数估计,以此为基础构建金融有向网络,进而对中国金融机构系统性风险传染效应进行实证分析。实证研究表明：(1)以单指标非对称CoVaR为代表的金融机构风险指标与网络舆情的协同变化趋势明显;(2)证券类和银行类金融机构对外部风险非常敏感,极易受到其他金融机构的影响,也极易影响其他金融机构;(3)非银行类机构在风险积累阶段占据重要位置,银行在风险爆发时刻占据重要位置;(4)相对于非银行类金融机构,银行类机构具有较强的传染能力。